A local extremum is not necessarily a global extremum. A local extremum is a point where the function reaches a maximum or minimum value within a small neighborhood, but it may not be the highest or lowest point in the entire function. A global extremum, on the other hand, is the highest or lowest point in the entire function. Therefore, a local extremum may or may not be a global extremum, depending on the behavior of the function in the larger context. **

The task for the extremum problem in robot motion is to optimize a certain objective function, such as minimizing energy consumption or maximizing speed, while satisfying constraints such as avoiding obstacles or staying within a certain workspace. This involves finding the optimal trajectory or control inputs for the robot to achieve the desired goal. The extremum problem aims to find the best solution that maximizes or minimizes the objective function under the given constraints, leading to efficient and effective robot motion planning. **

Extremum problems are mathematical problems that involve finding the maximum or minimum value of a function. These problems typically involve optimizing a certain quantity, such as maximizing profit or minimizing cost. Extremum problems are commonly encountered in various fields such as economics, engineering, and physics, where finding the optimal solution is crucial for decision-making and problem-solving. The process of solving extremum problems often involves using calculus techniques such as differentiation to find critical points where the function reaches its maximum or minimum value. **

No, not all global extremum points are also local extremum points of polynomial functions. Global extremum points are the highest or lowest points on the entire function, while local extremum points are the highest or lowest points within a specific interval. A polynomial function can have global extremum points that are not local extremum points if the function continues to increase or decrease beyond the local extremum point. **

The extremum problem in robot motion involves finding the optimal path or trajectory for a robot to move from one point to another while minimizing or maximizing a certain criterion. This criterion could be the shortest distance, fastest time, least energy consumption, or any other objective function. The task description typically includes defining the start and end points, specifying any constraints such as obstacles or limitations on the robot's motion, and formulating the objective function to be optimized. The goal is to find the path or trajectory that best satisfies the given criteria while adhering to the specified constraints. **

A global extremum is the highest or lowest value of a function over its entire domain. For a function with a global maximum, there is no other point in the domain where the function takes a higher value. Similarly, for a function with a global minimum, there is no other point in the domain where the function takes a lower value. Global extrema are important in optimization problems and can provide valuable information about the behavior of a function. **

Extremum problems with constraints involve finding the maximum or minimum value of a function while satisfying certain constraints. These constraints can be inequalities or equalities that restrict the possible solutions to the problem. The goal is to optimize the function within the given constraints to find the best possible solution. Extremum problems with constraints are commonly encountered in various fields such as economics, engineering, and mathematics. **

Extremum problems in mathematics involve finding the maximum or minimum value of a function. These problems are often solved by taking the derivative of the function and setting it equal to zero to find critical points. By analyzing these critical points and the endpoints of the interval, one can determine the maximum or minimum value of the function. Extremum problems are commonly encountered in optimization, physics, economics, and engineering. **